scipyio

scipyio is a Python package that provides a collection of input‑output utilities tailored for scientific computing workflows that use the SciPy ecosystem. The library was introduced in 2022 as an open‑source extension to simplify reading, writing, and converting data formats commonly encountered in numerical analysis, signal processing, and statistical modeling. By building on NumPy’s array structures and SciPy’s sparse matrix types, scipyio enables seamless interoperability between file formats such as MATLAB .mat, HDF5, NetCDF, and various plain‑text representations without requiring explicit conversion code.

Key features include high‑level functions for loading and saving dense and sparse arrays, automatic detection of data types, and support for compression options in HDF5 and NetCDF containers. The package also offers utilities for handling complex‑valued datasets, preserving metadata, and performing batch processing of files through iterator‑based APIs. Compatibility with SciPy’s linear algebra, optimization, and signal modules allows users to pass I/O objects directly into analytical pipelines.

The development of scipyio is coordinated on GitHub, where contributions follow the SciPy community’s governance model and code‑review practices. Documentation is hosted on Read the Docs and includes a reference guide, tutorial notebooks, and examples that demonstrate integration with popular scientific libraries such as pandas, xarray, and matplotlib. scipyio is distributed via the Python Package Index under the BSD‑3‑Clause license, and supports Python versions 3.8 and later on major operating systems including Linux, macOS, and Windows. Ongoing work focuses on extending format support, improving performance for large‑scale datasets, and enhancing compatibility with emerging scientific data standards.